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Conducting thematic analysis in qualitative research can be laborious and time-consuming. We propose and evaluate the feasibility of using Generative Pre-trained Transformer (GPT) models to assist public health researchers in extracting themes from interview transcripts. Carefully engineered prompts were used to sequentially extract and synthesize transcripts into a concise set of study-level themes relevant to the study’s goals. An evaluation using a 5-point Likert scale (0−4) assessed GPT-generated themes across 11 published studies based on four criteria: succinctness, alignment with researcher-identified themes, quality of explanations, and relevance of quotes. Across all four criteria, the scores averaged 3.05 (95% Confidence Interval (CI): [2.93, 3.16]). Our findings indicate that at least half of the GPT-generated themes align with those in published studies, exhibiting succinctness with minimal repetition, substantial depth of explanations, and relevant quotations. Despite these promising results, practices such as complementing outputs with field-specific knowledge are recommended.

Abstract The widespread use of antibiotics has significantly increased their presence in aquatic environments, particularly in sensitive Karst River systems. In this study, the distribution and ecological, human health, and resistance selection risk assessment of 44 antibiotics in the typical Karst River, Lijiang River, were investigated during the influenza season, a period marked by heightened antibiotic usage. 27 antibiotics could be found in the water of Lijiang River, among which azithromycin showing the highest concentrations. The concentrations of total antibiotics were in the range 171.70–2003.75 ng/L, with an average value of 704.76 ng/L. Macrolide was the predominant class, constituting an average of 57.65% of the total antibiotic concentrations. Risk assessments revealed that certain antibiotics, especially macrolides, posed moderate to high ecological risks to algae, displayed potential human health risks at low levels and contributed to antimicrobial resistance. Among all the antibiotics, azithromycin was the only one could cause ecological risk to algae, human health risk towards infants and antimicrobial resistance selection risk, which should be identified as the priority antibiotic for control in the Lijiang River during the influenza season. There was no difference in the concentrations, human health and antimicrobial resistance selection risk of antibiotics between mainstream and tributaries of Lijiang River. This study contributes to a better understanding of antibiotic pollution and provides insights into potential risk management practices in vulnerable aquatic systems worldwide.

Plastic pollution and its potential risks have been raising public concerns as a global environmental issue. Global plastic waste may double by 2030, posing a significant challenge to the remediation of environmental plastics. In addition to finding alternative products and managing plastic emission sources, effective removal technologies are crucial to mitigate the negative impact of plastic pollution. However, current remediation strategies, including physical, chemical, and biological measures, are unable to compete with the surging amounts of plastics entering the environment. This perspective lays out recent advances to propel both research and action. In this process, phytoaccumulation, phytostabilization, and phytofiltration can be applied to reduce the concentration of nanoplastics and submicron plastics in terrestrial, aquatic, and atmospheric environments, as well as to prevent the transport of microplastics from sources to sinks. Meanwhile, advocating for a more promising future still requires significant efforts in screening hyperaccumulators, coupling multiple measures, and recycling stabilized plastics from plants. Phytoremediation can be an excellent strategy to alleviate global micro/nanoplastic pollution because of the cost-effectiveness and environmental sustainability of green technologies.

Purpose: To report a rare case of Vogt-Koyanagi-Harada (VKH) disease complicated by unilateral focal choroidal excavation (FCE). Methods: A 25-year-old male patient with bilateral blurred vision, tinnitus, and headache. Initial examination revealed multiple sensory retinal detachments in both eyes. Optical coherence tomography (OCT), fundus fluorescein angiography (FFA), and other diagnostic tests confirmed VKH. The patient was treated with intravenous methylprednisolone followed by oral prednisolone. Results: Following treatment, the exudative retinal detachments resolved, and a subfoveal FCE was observed in the right eye. OCT imaging revealed choroidal inflammation and retinal pigment epithelium (RPE) disruption. The patient's visual acuity improved, but the FCE persisted during follow-up, suggesting a potential association between inflammation and the development of FCE in VKH. Conclusions: This case highlights the rare occurrence of FCE during the course of VKH disease, suggesting that inflammatory disruption of the RPE and choroidal atrophy may contribute to FCE formation. Comprehensive retinal imaging in VKH patients is essential for detecting such complications, which may influence long-term visual outcomes. This case adds to the limited literature on the relationship between ocular inflammation and choroidal excavation, providing valuable insights for future clinical management.

Purpose: This scoping review aimed to offer researchers and practitioners an understanding of artificial intelligence (AI) applications in physical activity (PA) interventions; introduce them to prevalent machine learning (ML), deep learning (DL), and reinforcement learning (RL) algorithms; and encourage the adoption of AI methodologies. Methods: A scoping review was performed in PubMed, Web of Science, Cochrane Library, and EBSCO focusing on AI applications for promoting PA or predicting related behavioral or health outcomes. AI methodologies were summarized and categorized to identify synergies, patterns, and trends informing future research. Additionally, a concise primer on predominant AI methodologies within the realm of PA was provided to bolster understanding and broader application. Results: The review included 24 studies that met the predetermined eligibility criteria. AI models were found effective in detecting significant patterns of PA behavior and associations between specific factors and intervention outcomes. Most studies comparing AI models to traditional statistical approaches reported higher prediction accuracy for AI models on test data. Comparisons of different AI models yielded mixed results, likely due to model performance being highly dependent on the dataset and task. An increasing trend of adopting state-of-the-art DL and RL models over standard ML was observed, addressing complex human–machine communication, behavior modification, and decision-making tasks. Six key areas for future AI adoption in PA interventions emerged: personalized PA interventions, real-time monitoring and adaptation, integration of multimodal data sources, evaluation of intervention effectiveness, expanding access to PA interventions, and predicting and preventing injuries. Conclusion: The scoping review highlights the potential of AI methodologies for advancing PA interventions. As the field progresses, staying informed and exploring emerging AI-driven strategies is essential for achieving significant improvements in PA interventions and fostering overall well-being.

Using simulated patients to mimic 9 established noncommunicable and infectious diseases, we assessed ChatGPT’s performance in treatment recommendations for common diseases in low- and middle-income countries. ChatGPT had a high level of accuracy in both correct diagnoses (20/27, 74%) and medication prescriptions (22/27, 82%) but a concerning level of unnecessary or harmful medications (23/27, 85%) even with correct diagnoses. ChatGPT performed better in managing noncommunicable diseases than infectious ones. These results highlight the need for cautious AI integration in health care systems to ensure quality and safety.

Antibiotic resistance is an escalating global health concern, exacerbated by the pervasive presence of antibiotic resistance genes (ARGs) in natural environments. The Yangtze River, the world's third-longest river, traversing areas with intense human activities, presents a unique ecosystem for studying the impact of these genes on human health. Here, we explored ARGs in the Yangtze River, examining 204 samples from six distinct habitats of approximately 6000 km of the river, including free-living and particle-associated settings, surface and bottom sediments, and surface and bottom bank soils. Employing shotgun sequencing, we generated an average of 13.69 Gb reads per sample. Our findings revealed a significantly higher abundance and diversity of ARGs in water-borne bacteria compared to other habitats. A notable pattern of resistome coalescence was observed within similar habitat types. In addition, we developed a framework for ranking the risk of ARG and a corresponding method for calculating the risk index. Applying them, we identified water-borne bacteria as the highest contributors to health risks, and noted an increase in ARG risks in particle-associated bacteria correlating with heightened anthropogenic activities. Further analysis using a weighted ARG risk index pinpointed the Chengdu–Chongqing and Yangtze River Delta urban agglomerations as regions of elevated health risk. These insights provide a critical new perspective on ARG health risk assessment, highlighting the urgent need for strategies to mitigate the impact of ARGs on human health and to preserve the ecological and economic sustainability of the Yangtze River for future human use.

AlFuMoF was obtained by purifying the secondary aluminum ash and using hydrothermal method and modification treatment. Next, using the β-Cyclodextrin impregnation treatment AlFuMoF, a modified MOF (β-CD@AlFuMoF) was obtained. Both MOFs were subsequently characterized, and their potential for adsorption of fluoride from wastewater was compared. The characterization was performed by SEM, EDS, FTIR, XRD, particle size change and thermogravimetric. The adsorption characteristics of AlFuMoF and β-CD@AlFuMoF under different conditions of pH, contact time as well as initial concentration were evaluated using kinetic and thermodynamic studies and adsorption isotherms. In terms of dynamics, the pseudo second order model fits the experimental data best. According to the Langmuir model, the maximum fluoride adsorption capacity of AlFuMoF and β-CD@AlFuMoF are 22.56 and 39.95 mg g−1, respectively. Thermodynamic studies show that the adsorption of fluoride on AlFuMoF and β-CD@AlFuMoF are spontaneous and mainly controlled by chemical adsorption. According to the findings, β-CD modification of AlFuMoF can be considered as a promising method for removing fluoride from wastewater.

Abstract Deciphering biogeographic patterns of microorganisms is important for evaluating the maintenance of microbial diversity with respect to the ecosystem functions they drives. However, ecological processes shaping distribution patterns of microorganisms across large spatial‐scale watersheds remain largely unknown. Using Illumina sequencing and multiple statistical methods, we characterized distribution patterns and maintenance diversity of microorganisms (i.e., archaea, bacteria, and fungi) in soils and sediments along the Yangtze River. Distinct microbial distribution patterns were found between soils and sediments, and microbial community similarity significantly decreased with increasing geographical distance. Physicochemical properties showed a larger effect on microbial community composition than geospatial and climatic factors. Archaea and fungi displayed stronger species replacements and weaker environmental constraints in soils than that in sediments, but opposite for bacteria. Archaea, bacteria, and fungi in soils showed broader environmental breadths and stronger phylogenetic signals compared to those in sediments, suggesting stronger environmental adaptation. Stochasticity dominated community assemblies of archaea and fungi in soils and sediments, whereas determinism dominated bacterial community assembly. Our results have therefore highlighted distinct microbial distribution patterns and diversity maintenance mechanisms between soils and sediments, and emphasized important roles of species replacement, environmental adaptability, and ecological assembly processes on microbial landscape. Our findings are helpful in predicting loss of microbial diversity in the Yangtze River Basin, and might assist the establishment of environmental policies for protecting fragile watersheds.

The presence of antibiotic resistance genes (ARGs) and antibiotic-resistant bacteria (ARB) in the environment is of great concern to human health. This study developed a new combination of high-frequency electromagnetic field (HEMF) and low-dosage chlorine disinfection to reduce the abundance of extracellular ARG (eARG) sul2 and intracellular ARG (iARG) adeF. The removal efficiencies of sul2 and adeF from sulfamethoxazole- and multidrug-resistant Acinetobacter junii were measured by quantitative PCR (qPCR). Compared to chlorine disinfection alone, the combination of HEMF treatment exhibited significantly improved ARG removal efficiency. The highest removal efficiencies of sul2 and adeF under the combination were 75.7% and 91.4%, respectively. Treatment time and the dosage of chlorine played pivotal roles in the removal efficiency of ARGs via HEMF treatment and chlorine disinfection, respectively. Importantly, a combination of low-dose chlorine with HEMF treatment could serve as a viable alternative to high-dose chlorine disinfection. This work offers essential process parameters for optimizing the elimination of iARGs and eARGs and presents a viable solution for addressing the issue of ARG contamination.

As the Chat Generative Pre-trained Transformer (ChatGPT) achieves increased proficiency in diverse language tasks, its potential implications for academic integrity and plagiarism risks have become concerning. Traditional plagiarism detection tools primarily analyze text passages, which may fall short when identifying machine-generated text. This study aims to introduce a method that uses both prompts and essays to differentiate between machine-generated and human-written text, with the goal of enhancing classification accuracy and addressing concerns of academic integrity. Leveraging a dataset of student-written essays responding to eight distinct prompts, we generated comparable essays with ChatGPT. Similarity scores within machine-generated essays (“within” scores) and between human-written and machine-generated essays (“between” scores) were computed. Subsequently, we used the percentile scores of the “between” scores within the “within” scores distribution to gauge the probability of an essay being machine-generated. Our proposed method achieved high classification accuracy, with an AUC score of 0.991, a false positive rate of 0.01, and a false negative rate of 0.037 in the test set. This validates its effectiveness in distinguishing between machine-generated and human-written essays and shows that it outperforms existing approaches based solely on text passages. This research presents a straightforward and effective method to detect machine-generated essays using prompts, providing a reliable solution to maintain academic integrity in the era of advanced language models like ChatGPT. Nevertheless, the method is not without its limitations, warranting further research to investigate its performance across diverse educational contexts, various prompts, and different model hyperparameters.

Abstract Background Riverine ecosystems are one of the most important reservoirs of antibiotic resistance genes (ARGs) in the environment, but the occurrence and controlling factors of ARG distribution in different habitats of riverine ecosystems remain poorly understood. In this study, a metagenomic approach was used to characterize ARG types and their abundance in different habitats (rhizosphere soil, surface bulk soil, bottom bulk soil, and sediment) of riverine ecosystems in eastern China. Sampling sites were located along different rivers of eastern China, which are geographically isolated. Differences in bacterial communities, mobile genetic elements (MGEs), pattern and intensity of human activities, climate, and other environmental factors at the sampling sites and habitats were expected to affect ARG occurrence. Results ARGs were observed with high variations in diversity (44–206 subtypes) and abundance (6.85–105.68 ×/Gb). There were significant south-north differences in ARG occurrence in the same habitat, except for surface bulk soil. And the significant difference was found in ARGs among four southern habitats. South–north differences in ARGs of the same habitat were mainly attributed to the combination of different occurrence frequencies and habitat selections of ARGs. Differences in ARG profiles among the four habitats in the south and the north were both mainly attributed to the different occurrence frequencies of ARGs. Bacterial communities and MGEs (Mobile genetic elements) could account for the observed variance in the resistome of riverine ecosystems across eastern China. The co-occurrences of specific ARGs with bacterial communities and MGEs were more frequent at the northern sampling sites than in the south, and co-occurrence patterns (i.e. ARGs and bacterial communities or ARGs and MGEs) varied between the habitats. Moreover, building land in all habitats, except bulk soils, showed significant positive correlations with ARG abundance. Conclusion This study reveals a high variance in the resistome of riverine ecosystems in eastern China and its controlling factors. We appeal to the importance of assessment of ARGs in the riverine ecosystem and the need for future prevention and intervention of ARG spread.

Deciphering biogeographical patterns of alkaline phosphatase (phoD)-harboring bacteria is essential to understand organic phosphorus mineralization. However, it is poorly understood about distribution pattern and diversity maintenance mechanisms of phoD-harboring bacteria (PHB) in watershed ecosystems. Here, we estimated ecological processes shaping landscape of PHB in soils and sediments along the Yangtze River. The PHB community similarity decayed against higher geographical distance at taxonomic and phylogenetic levels, and larger compositional variation in PHB community were found in sediments only. The PHB displayed higher α-diversities, broader environmental breadths, higher community stability, and stronger species replacement in soils. Conversely, PHB showed stronger phylogenetic signals in sediments. Stochastic and differentiating processes dominated community assemblies of PHB in both soils and sediments. Electrical conductivity displayed decisive roles in shaping PHB diversity for soils and sediments at taxonomic and phylogenetic levels. Our results emphasized differences in distribution patterns of PHB between soils and sediments, and highlighted ecological processes shaping landscapes of PHB in soils and sediments along the Yangtze River. The phosphorus cycling-related findings might be helpful to estimate ecological potential of a watershed ecosystem and could provide new insights for ecological protection policy for the Yangtze River.

In this study, SAA@CS-CB(aluminum-ash carbide slag carbon black doped composite) was prepared by sintering method and modified by impregnation with oxalic acid to obtain SAA@CS-CBoa. Fluoride adsorption experiments were carried out using this composite as adsorbent. With increasing pH values, the adsorption amount of fluoride decreases in the range of 2–11. The pseudo second order equation and Langmuir model were fit to the experimental data, and the adsorption of fluoride by SAA@CS-CBoa exhibited spontaneous and endothermic characteristics. When PO43-, CO32–, SO42-, Cl-, NO3–, Br- and HCO3– anions were individually or combined in solution, the adsorbents exhibited higher fluoride selectivity and sensitivity, while PO43-and CO32– weakened the adsorption of fluoride in solution in the same way regardless of the presence of the other 5 anions. The results of SEM, EDS, XRD and FTIR characterizations showed that the mechanism of fluoride adsorption and removal by SAA@CS-CBoa included the combined effects of electrostatic attraction, surface coordination precipitation and ion exchange. SAA@CS-CBoa is an effective composite material for water adsorption of fluoride, and still has an excellent performance of cyclic regeneration after 10 times adsorption desorption. This study provides a new approach for the utilization of fluoride removal resources for industrial solid waste resource recycling.

PAHs are one of the environmental contaminants of greatest concern on global scales due to their ecological risk. This study collected the polycyclic aromatic hydrocarbon (PAH) concentration data of six different media in Kenya and evaluated their ecological risk assessment. Twenty-five literatures related to PAHs pollution in Kenya were found to conduct a meta-analysis. Our meta-analysis shows that the geometric means of PAH pollution in water (481.49 ng L−1), sediment (519.15 ng g−1) t, soil (337.46 ng g−1), air (38.60 ng m−3), food (33.12 ng g−1), and other (111,176.90 ng g−1) six media in Kenya had different degrees. The primary sources were combustion sources. A small number of PAHs are petroleum sources. A variety of methods were used to assess the ecological risk of PAHs in different media in Kenya, and we used a tiered approach to assess the ecological risk of water.The risk assessment result showed that the high contamination of Acenaphthylene and Acenaphthelene found in water in Kenya may pose certain ecological risks, which requires necessary measures. The concentration of Benzo[k]fluoranthene in sediment and the concentration of carcinogenic PAHs in soil can also cause the ecological risks, which should be paid more attention. In light of the PAH contamination in various media found in Kenya in the study, further detailed studies should be carried out to provide a more detailed analysis of the distribution of PAHs in Kenya to prevent the severe impact of PAHs contamination in Kenya and Africa.

Abstract LIM and SH3 protein 1 (LASP1) is a metastasis-related protein reported to enhance tumor progression in colorectal cancer (CRC). However, the underlying mechanism is still elusive. The chaperonin protein containing TCP1 (CCT) is a cellular molecular chaperone complex, which is necessary for the correct folding of many proteins. It contains eight subunits, CCT1-8. CCT8 is overexpressed in many cancers, however, studies on CCT8 are limited and its role on CRC development and progression remains elusive. In this study, we confirmed that CCT8 and LASP1 can interact with each other and express positively in CRC cells. CCT8 could recover the ability of LASP1 to promote the invasion of CRC; CCT8 could significantly promote the proliferation, invasion, and metastasis of colorectal cells in vivo and in vitro. Mechanically, CCT8 inhibited the entry of WTp53 into the nucleus, and there was a negative correlation between the expression of CCT8 and the nuclear expression of WTp53 in clinical colorectal tissues. CCT8 promoted the cell cycle evolution and EMT progression of CRC by inhibiting the entry of WTp53 into the nucleus. Clinically, CCT8 was highly expressed in CRC. More importantly, the overall survival of CRC patients with high expression of CCT8 was worse than that of patients with low expression of CCT8. These findings indicate that as LASP1-modulated proteins, CCT8 plays a key role in promoting the progression of colorectal cancer, which provides a potential target for clinical intervention in patients with colorectal cancer.

The aquatic environment is an important medium for the accumulation and dissemination of antibiotic-resistant bacteria as it is often closely related to human activities. Previous studies paid little attention to the prevalence and mechanism of polymyxin-resistant bacteria in the aquatic environment. As a Gram-negative opportunistic pathogen widely distributed in aquatic ecosystems, the antibiotic-resistant profile of Aeromonas spp. deserves much attention. In this study, we identified 61 Aeromonas spp. isolates from water samples in the section of the Yangtze River. The total polymyxin B (PMB) resistance rate of these strains was 49.18% (30/61), showing a high level of polymyxin resistance in Aeromonas spp. The MIC50 and MIC90 for PMB exhibited a significant discrepancy among different species (p

Rivers play an important role in receiving and transporting the resistome among different environmental compartments. However, the difference in resistome and mobilome between the water and sediment and their underlying mechanisms were still poorly understood. In this study, the Ili River, an important water source in the arid area of Central Asia, was selected as the studied target. The comprehensive profile of resistome and mobilome and their host in water and sediment were studied based on metagenomic binning and assembled genome (MAG) analysis. The relative abundance of resistome and mobilome in sediment were 28.0 – 67.8 × /Gb and 46.5 – 121.1 × /Gb, respectively, which were significantly higher than those in water (23.1 – 52.8 ×/Gb and 25.3 – 67.7 ×/Gb). Multidrug and macrolides-lincosamides-streptogramin (MLS) resistance genes were the main ARG types in both water and sediment from relative abundance. Transposases dominated the relative abundance of mobilome, followed by insert elements and integrases. Strong correlations were found between the relative abundance of resistome and mobilome (r > 0.6 and p

C-SAAoa particles synthesized by simple and low-cost calcining industrial solid waste aluminium ash combined with waste oxalic acid modification process show excellent performance in fluoride removal speed and adsorption capacity. Their adsorption capacity on fluoride was determined at about 180.57 mg/g at pH 3.0, which was among the highest reported values in the literature. It was determined that the adsorption mechanism of fluoride on C-SAAoa particles followed mechanisms such as ion exchange, electrostatic action, and the surface - OH groups played a major role in the fluoride removal process. C-SAAoa particles can effectively remove fluoride, even in the presence of a certain concentration of competing anions. At the same time, the material possesses good cycling performance, and can still maintain 78.9% of the initial adsorption capacity in the longitudinal for eight recycles. Therefore, it may have the potential to become a promising adsorbent as a supplement to industrial solid waste resource-based utilization processes and also for fluoride removal in small-scale treatment facilities or wastewater with high fluoride concentrations.

Abuse of heavy metals and antibiotics results in the dissemination of metal resistance genes (MRGs) and antibiotic resistance genes (ARGs). Ditch wetlands are important sinks for heavy metals and antibiotics. The relationships between bacterial communities and MRG/ARG dissemination under dual stresses of heavy metals and antibiotics remain unclear. The responses of MRGs and ARGs to the co-selective pressure of cadmium (Cd) and doxycycline (DC) in ditch wetlands were investigated after 7-day and 84-day exposures. In ecological ditches, residual rates of Cd and DC varied from 0.4 to –5.73% and 0 to –0.61%, respectively. The greatest total relative abundance of ARGs was observed in the Cd 5 mg L–1 + DC 50 mg L–1 group. A significant level of DC (50 mg L–1) significantly reduced the total relative abundances of MRGs at a concentration of 5 mg L–1 Cd stress. Redundancy analysis indicated that Cd and DC had strong positive effects on most ARGs and MRGs after a 7-day exposure. Meanwhile, the class 1 integron gene (intI1) exhibited strong positive correlations with most ARGs and cadmium resistance genes (czcA) after an 84-day exposure. Network analysis showed that Acinetobacter and Pseudomonas were the potential dominant host genera for ARGs and MRGs, and tetracycline resistance genes (tetA), czcA, and intI1 shared the same potential host bacteria Trichococcus after an 84-day exposure.

The performance of underwater target detection algorithms is affected by poor imaging quality in underwater environments. Due to the arithmetic power limitation of underwater devices, existing deep learning networks are unable to provide efficient detection processes with high detection accuracy. Lightweight CNN models have been actively applied for underwater environment detection, yet their lite feature fusion networks cannot provide effective fusion effects and reduce the detection accuracy. In this paper, a lightweight algorithm based on multi-scale feature fusion was proposed, with the model parameters greatly reduced, improving the target detection accuracy. The forward propagation memory overhead is reduced by using multi-scale shared convolutional kernels and pooling operations to co-construct the query matrix in the Tansformer encoding stage. Then, the feature fusion path is optimized in order to enhance the connection of multi-scale features. A multiscale feature adaptive fusion strategy is used to enhance the detection performance and reduce the dependence on the complex feature extraction network. The feature extraction network is also reparameterized to simplify the operation. Using the UPRC offshore dataset for validation, the study results have demonstrated that the statistical mAP metrics validate the detection accuracy. Compared with SSD, RetinaNet and YOLOv5-s improved by 13%, 8.6%, and 0.8%, while the number of parameters decreased by 76.09%, 89.74%, and 87.67%. In addition, compared with the YOLOv5-lite model algorithm with the same parameter volume, the mAP is improved by 3.8%, which verifies the accuracy and efficiency of the algorithm in this paper.

Underwater robot perception is a critical task. Due to the complex underwater environment and low quality of optical images, it is difficult to obtain accurate and stable target position information using traditional methods, making it unable to meet practical use requirements. The relatively low computing power of underwater robots prevents them from supporting real-time detection with complex model algorithms for deep learning. To resolve the above problems, a lightweight underwater target detection and recognition algorithm based on knowledge distillation optimization is proposed based on the YOLOv5-lite model. Firstly, a dynamic sampling Transformer module is proposed. After the feature matrix is sparsely sampled, the query matrix is dynamically shifted to achieve the purpose of targeted attention modeling. Additionally, the shared kernel parameter convolution is used to optimize the matrix encoding and simplify the forward-propagation memory overhead. Then, a distillation method with decoupled localization and recognition is designed in the model-training process. The ability to transfer the effective localization knowledge of the positive sample boxes is enhanced, which ensures that the model maintains the same number of parameters to improve the detection accuracy. Validated by real offshore underwater image data, the experimental results show that our method provides an improvement of 6.6% and 5.0% over both baseline networks with different complexity models under the statistical index of detection accuracy mAP, which also suggests 58.8% better efficiency than models such as the standard YOLOv5. Through a comparison with other mainstream single-stage networks, the effectiveness and sophistication of the proposed algorithm are validated.

A global survey was performed with 122 aquatic metagenomic DNA datasets (92 lake water and 30 seawater) obtained from the Sequence Read Archive (SRA). Antibiotic resistance genes (ARGs) and metal resistance genes (MRGs) were derived from the dataset sequences via bioinformatic analysis. The relative abundances of ARGs and MRGs in lake samples were in the ranges ND (not detected)–1.34 × 100 and 1.22 × 10−3–1.98 × 10−1 copies per 16S rRNA, which were higher than those in seawater samples. Among ARGs, multidrug resistance genes and bacitracin resistance genes had high relative abundances in both lake and sea water samples. Multi-metal resistance genes, mercury resistance genes and copper resistance genes had the greatest relative abundance for MRGs. No significant difference was found between epilimnion and hypolimnion in abundance or the Shannon diversity index for ARGs and MRGs. Principal coordinates analysis and permutational multivariate analysis of variance (PERMANOVA) test showed that stratification and geography had significant influence on the composition of ARGs and MRGs in lakes (p

The increasing prevalence of antibiotic resistance genes (ARGs) in aquatic environments has attracted considerable concerns due to their potential threat to public health. For reducing environmental risk of ARGs, it is crucial to identify the pathogenic resistant bacteria, determine the driving forces governing the ARG community and apportion their sources, which is yet remained to explore. In this study, we developed a framework integrating high-throughput sequencing (HTS) analyses, null-model-based methods and machine-learning classification tool for understanding the environmental resistome risk and the ecological processes that control the ARG profile in aquatic sediments, and applied to two urban lakes (Lake Tai and Lake Baiyang) in China. The HTS-based metagenomic analyses revealed abundant and diverse resistome, mobilome and virulome in the two lakes, including some emerging ARGs such as mcr and carbapenemases types. Relatively, the diversities for ARGs, mobile genetic elements (MGEs) and virulence factor genes in Lake Baiyang were significantly higher than those in Lake Tai (p 65%). This was confirmed by the determination analyses of various ecological processes on ARG community by utilizing the null-model-based statistical framework for quantifying community assembly. That is, homogenizing dispersal (40%) dominated in Lake Baiyang, followed by homogeneous selection (32%) and ecological drift (15%), while ecological drift (33%) and homogenizing dispersal (31%) were the dominators in Lake Baiyang. SourceTracker analysis showed human sewage-associated sources were the largest contributor (~62%) of ARGs in the environment. The findings shed light on the dissemination risk and driver dynamics of antimicrobial resistance in the aquatic environment, which may help to make effective management strategies for controlling pollution of ARGs.

Terrestrial cyanobacteria Nostoc commune is an ideal species to study the geographical variation of mineral elements of soil cyanobacteria at the species level. Here, we first address the following questions: (1) from where are these mineral elements, (2) are there geographical variations for these mineral elements, and if so, (3) which environmental factors drive the geographical variation of these mineral elements? Second, we tested whether the soil cyanobacterial mineral elements followed the “restrictive element stability hypothesis” of higher plants. Finally, we explored the effect of mineral geographic variation on ecological adaptation of soil cyanobacteria. We collected N. commune samples across gradients of climate, soil, and atmospheric wet deposition mineral concentration in mainland China. We measured fifteen minerals, including five macroelements (N, Ca, K, Fe, P), five microelements (Mn, Zn, Cu, Co, Se), and five heavy metals (Pb, Cr, As, Cd, Hg). We found that five elements (P, Cu, Zn, Co, Pb) had significant geographical variation. They increased as the distance from the equator increased and decreased as the distance from the prime meridian increased. Mean annual precipitation and mean annual temperature explained most of the variation. We did not find any significant correlations between the mineral element contents in N. commune and the minerals in soil and rainfall, except for P. There was no significant correlation between the variation coefficients of different elements and their actual detected contents and their potential physiological required contents. The statistical results of our experiment did not support the “restrictive element stability hypothesis.” We speculated that net accumulation of mineral elements in cyanobacterial cells and extracellular polysaccharides (EPS) might play an important role for terrestrial cyanobacteria in the adaptation to dry and cold conditions.

Antibiotic and metal resistance genes (ARGs and MRGs) in tap water are of great public health concern. However, very fewer studies focused on the relationship between resistance genes and opportunistic pathogens in tap water. In this study, the diversity and abundance of resistance genes and bacterial community from tap water at a large-scale along the middle and lower reaches of the Yangtze River were investigated. The total relative abundances of ARGs and MRGs were 2.95 × 10−3–1.22 × 10−1 and 1.93 × 10−3–1.20 × 10−1 copies/16S rRNA, respectively. The blaTEM and merP detected were major ARG and MRG subtypes, respectively. Mobile genetic elements (Intl1 and tnpA) showed significant correlations with the abundance of ARGs. Heavy metals also played a vital role in the co-selection of ARGs. Surprisingly, there were still eight opportunistic pathogens in tap water, among which Escherichia coli, Helicobacter pylori, Mycoplasma pneumoniae, and Porphyromonas gingivalis were the potential host of ARGs and MRGs. Escherichia coli had the highest abundance, while Bacillus anthracis had the highest detected frequency (100%), a widespread opportunistic pathogen in tap water.

Plastics have been accumulated offshore and in the deep oceans at an unprecedented scale. Microbial communities have colonized the plastisphere, which has become a reservoir for both antibiotic and metal resistance genes (ARGs and MRGs). This is the first analysis of the diversity, abundance, and co-occurrence of ARGs and MRGs, and their relationships within the microbial community, using metagenomic data of plastic particles observed in the North Pacific Gyre obtained from the National Centre for Biotechnology Information Sequence Read Archive database. The abundance of ARGs and MRGs in microbial communities on the plastics were in the ranges 7.07 × 10−4–1.21 × 10−2 and 5.51 × 10−3–4.82 × 10−2 copies per 16S rRNA, respectively. Both the Shannon-Wiener indices and richness of ARGs and MRGs in plastics microbiota were significantly greater than those of ARGs and MRGs in seawater microbiota in the North Pacific Gyre via one-way analysis of variance. Multidrug resistance genes and multi-metal resistance genes were the main classes of genes detected in plastic microbiota. There were no significant differences in the abundance or diversity of ARGs and MRGs between macroplastics biota and microplastics biota, indicating that particle size had no effect on resistance genes. Procrustes analysis suggested that microbial community composition was the determining factor of the ARG profile but not for MRG. Some ARGs and MRGs had a higher incidence of non-random co-occurrence, suggesting that the co-effects of selection for antibiotic or metal resistance are important factors influencing the resistome of the microbiota on the plastic particles. Keywords: Metagenomic analysis, Pacific Ocean, Microplastics, Macroplastics, Resistance genes

In the Tibetan agro-pastoral ecotone, which has an altitude of 4000 m above sea level, small-scale cropland tillage has been exploited on the grassland surrounding the houses of farmers and herdsmen. However, knowledge of the effects of land change from grassland to cropland on soil nutrients and microbial communities is poor. Here, we investigated the structure and assembly mechanism of bacterial communities in cropland (tillage) and grassland (non-tillage) from an agro-pastoral ecotone of Tibet. Results indicated that soil nutrients and composition of bacterial communities changed dramatically in the process of land-use change from grassland to cropland. The pH value and the content of total nitrogen, organic material, total potassium, and total phosphorus in cropland soil were well above those in grassland soil, whereas the soil bulk density and ammonia nitrogen content in grassland soil were higher than those in cropland soil. Proteobacteria (30.5%) and Acidobacteria (21.7%) were the key components in cropland soil, whereas Proteobacteria (31.5%) and Actinobacteria (27.7%) were the main components in grassland soils. Tillage promotes uniformity of bacterial communities in cropland soils. In particular, the higher migration rate may increase the coexistence patterns of the bacterial community in cropland soils. These results also suggest that the tillage promotes the migration and coexistence of bacterial communities in the grassland soil of an agro-pastoral ecotone. In addition, the stochastic process was the dominant assembly pattern of the bacterial community in cropland, whereas, in grassland soil, the community assembly was more deterministic. These findings provide new insights into the changes in soil nutrients and microbial communities during the conversion of grassland to cropland in the agro-pastoral ecotone.

Phosphogypsum (PG) treatment is one of the research hotspots in the field of environmental protection. Many researchers both at home and abroad have devoted themselves to studies on harmless resource treatment of PG, but the treatment technology is unable to meet the demand of PG consumption due to the huge production and storage demands. In order to solve the problem of PG pollution, this study explored the different solidified effects of various modification formulations on the hazardous components in PG, using industrial solid waste calcium carbide slag (CCS) as an alkaline regulator; Portland cement (PC), polyaluminum chloride (PAC) and CaCl2 as the main raw materials of the solidification and stabilization formula and the water content in PG as the reaction medium. The results showed that CCS (0.5%), PC (0.4%) and PAC (0.3%) had a more significant solidified effect on phosphorus (P) and fluoride (F). PAC was added in two steps and reacted under normal temperature and pressure, and its leaching toxicity meets the requirements of relevant standards, which laid an excellent foundation for PG-based ecological restoration materials and filling materials, with low economic cost, simple process and strong feasibility. This will provide great convenience for the later mining and metallurgy.

The ~350 km2 water level fluctuation zone (WLFZ) in the Three Gorges Reservoir (TGR) of China, situated at the intersection of terrestrial and aquatic ecosystems, experiences a great hydrological change with prolonged winter inundation. Soil samples were collected in 12 sites pre- (September 2008) and post submergence (June 2009) in the WLFZ and analyzed for soil nutrients. Self-organizing map (SOM) and statistical analysis including multi-way ANOVA, paired-T test, and stepwise least squares multiple regression were employed to determine the spatio-temporal variations of soil nutrients in relation to submergence, and their correlations with soil physical characteristics. Results showed significant spatial variability in nutrients along ~600 km long shoreline of the TGR before and after submergence. There were higher contents of organic matter, total nitrogen (TN), and nitrate (NO3-) in the lower reach and total phosphorus (TP) in the upper reach that were primarily due to the spatial variations in soil particle size composition and anthropogenic activities. Submergence enhanced soil available potassium (K), while significantly decreased soil N, possibly due to the alterations of soil particle size composition and increase in soil pH. In addition, SOM analysis determined important roles of soil pH value, bulk density, soil particle size (i.e., silt and sand) and nutrients (TP, TK, and AK) on the spatial and temporal variations in soil quality. Our results suggest that urban sewage and agricultural runoffs are primary pollutants that affect soil nutrients in the WLFZ of TGR.

This study was designed to determine concentrations of polycyclic aromatic hydrocarbons (PAHs) in soil samples collected from Midway Atoll and evaluate their potential risks to human health. The total concentrations of 16 PAHs ranged from 3.55 to 3200 µg kg(-1) with a mean concentration of 198 µg kg(-1). Higher molecular weight PAHs (4-6 ring PAHs) dominated the PAH profiles, accounting for 83.3% of total PAH mass. PAH diagnostic ratio analysis indicated that primary sources of PAHs in Midway Atoll could be combustion. The benzo[a]pyrene equivalent concentration (BaPeq) in most of the study area (86.5%) was less than 40 µg kg(-1) BaPeq and total incremental lifetime cancer risks of PAHs ranged from 1.00×10(-10) to 9.20×10(-6) with a median value of 1.24×10(-7), indicating a minor carcinogenic risk of PAHs in Midway Atoll.

Terrestrial ecosystems are increasinglybeing exposedtometallicnanoparticles (MNPs). However, the global-scale impact of MNPs on soil carbon dioxide (CO2) emission remains unknown, limiting our understanding of the role of MNPs in global carbon cycle. We compiled a dataset comprising 1764 pairs of experimental observations to investigate the effects of MNPs exposure on soil respiration parameters, including respiration rates, related enzyme activities, and microbial variables. We found that MNPs could stimulate or suppress soil basal respiration rates across global environments, depending largely on the type of MNPs. We further showed that, although the inhibition of MNPs on most enzyme activities peaked in short-term exposure (≤28 days), prolonged exposure to MNPs still inhibited soil organic carbon degradation. Finally, we determined that environmental conditions (e.g., soil pH and presence/absence of plants) were also important regulators of the influence of MNPs on soil respiration parameters. Our findings underline that the effects of MNPs on soil CO2 emission depended on MNPs type, exposure design, and environmental factors, which is critical for predicting the role of MNPs in influencing the global carbon cycle and climate change. [ABSTRACT FROM AUTHOR]